[DOP-29498] Allow overriding Spark session config

docker/download_maven_packages.py

@@ -41,7 +41,7 @@ def get_worker_spark_session_for_docker(connection_types: set[str]) -> SparkSess
     """
     from pyspark.sql import SparkSession
 
-    spark_builder = SparkSession.builder.appName("syncmaster_jar_downloader").master("local")
+    spark_builder = SparkSession.builder.appName("syncmaster_jar_downloader").master("local[1]")
 
     for k, v in get_spark_session_conf_for_docker_image(connection_types).items():
         spark_builder = spark_builder.config(k, v)

docs/changelog/next_release/291.feature.rst

@@ -0,0 +1,12 @@
+Allow passing default Spark session config via worker settings:
+
+.. code-block:: yaml
+    :caption: config.yml
+
+    worker:
+        spark_session_default_config:
+            spark.master: local
+            spark.driver.host: 127.0.0.1
+            spark.driver.bindAddress: 0.0.0.0
+            spark.sql.pyspark.jvmStacktrace.enabled: true
+            spark.ui.enabled: false

docs/reference/worker/create_spark_session.rst

@@ -1,12 +1,32 @@
 .. _worker-create-spark-session:
 
-Altering Spark session settings
-===============================
+Configuring Spark session
+=========================
 
 SyncMaster Worker creates `SparkSession <https://spark.apache.org/docs/latest/sql-getting-started.html#starting-point-sparksession>`_ for each Run.
-By default, SparkSession is created with ``master=local``, all required .jar packages for specific DB/FileSystem types, and limiter by transfer resources.
 
-It is possible to alter SparkSession config by providing custom function:
+By default, SparkSession is created with ``master=local``, including all required .jar packages for DB/FileSystem types, and limited by transfer resources.
+
+Custom Spark session configuration
+----------------------------------
+
+It is possible to alter default `Spark Session configuration <https://spark.apache.org/docs/latest/configuration.html>`_ worker settings:
+
+.. code-block:: yaml
+    :caption: config.yml
+
+    worker:
+        spark_session_default_config:
+            spark.master: local
+            spark.driver.host: 127.0.0.1
+            spark.driver.bindAddress: 0.0.0.0
+            spark.sql.pyspark.jvmStacktrace.enabled: true
+            spark.ui.enabled: false
+
+Custom Spark session factory
+----------------------------
+
+It is also possible to use custom function which returns ``SparkSession`` object:
 
 .. code-block:: yaml
     :caption: config.yml
@@ -21,17 +41,19 @@ Here is a function example:
 
     from syncmaster.db.models import Run
     from syncmaster.dto.connections import ConnectionDTO
+    from syncmaster.worker.settings import WorkerSettings
     from pyspark.sql import SparkSession
 
     def create_custom_spark_session(
         run: Run,
         source: ConnectionDTO,
         target: ConnectionDTO,
+        settings: WorkerSettings,
     ) -> SparkSession:
         # any custom code returning SparkSession object
         return SparkSession.builde.config(...).getOrCreate()
 
-Module with custom function should be placed in the same Docker image or Python virtual environment used by SyncMaster worker.
+Module with custom function should be placed into the same Docker image or Python virtual environment used by SyncMaster worker.
 
 .. note::
 

syncmaster/worker/controller.py

@@ -203,10 +203,11 @@ def __init__(
     @slot
     def perform_transfer(self) -> None:
         try:
-            spark = self.settings.worker.CREATE_SPARK_SESSION_FUNCTION(
+            spark = self.settings.worker.create_spark_session_function(
                 run=self.run,
                 source=self.source_handler.connection_dto,
                 target=self.target_handler.connection_dto,
+                settings=self.settings.worker,
             )
 
             with spark:

syncmaster/worker/settings/__init__.py

@@ -1,5 +1,7 @@
 # SPDX-FileCopyrightText: 2023-2024 MTS PJSC
 # SPDX-License-Identifier: Apache-2.0
+from typing import Any
+
 from pydantic import BaseModel, Field
 from pydantic.types import ImportString
 
@@ -24,14 +26,25 @@ class WorkerSettings(BaseModel):
         :caption: config.yml
 
         worker:
-            log_url_template: https://logs.location.example.com/syncmaster-worker?correlation_id={{ correlation_id }}&run_id={{ run.id }}
+            log_url_template: "https://logs.location.example.com/syncmaster-worker?correlation_id={{ correlation_id }}&run_id={{ run.id }}"
+
             create_spark_session_function: custom_syncmaster.spark.get_worker_spark_session
+            spark_session_default_config:
+                spark.master: local
+                spark.driver.host: 127.0.0.1
+                spark.driver.bindAddress: 0.0.0.0
+                spark.sql.pyspark.jvmStacktrace.enabled: true
+                spark.ui.enabled: false
     """
 
-    CREATE_SPARK_SESSION_FUNCTION: ImportString = Field(
+    create_spark_session_function: ImportString = Field(
         "syncmaster.worker.spark.get_worker_spark_session",
         description="Function to create Spark session for worker",
     )
+    spark_session_default_config: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Default Spark session configuration",
+    )
     log_url_template: str = Field(
         "",
         description=":ref:`URL template to access worker logs <worker-log-url>`",

syncmaster/worker/spark.py

@@ -14,6 +14,7 @@
     HDFSConnectionDTO,
     HiveConnectionDTO,
 )
+from syncmaster.worker.settings import WorkerSettings
 
 if TYPE_CHECKING:
     from pyspark.sql import SparkSession
@@ -25,14 +26,18 @@ def get_worker_spark_session(
     run: Run,
     source: ConnectionDTO,
     target: ConnectionDTO,
+    settings: WorkerSettings,
 ) -> SparkSession:
     """Construct Spark Session using run parameters and application settings"""
     from pyspark.sql import SparkSession
 
     name = run.transfer.group.name + "_" + run.transfer.name  # noqa: WPS336
-    spark_builder = SparkSession.builder.appName(f"syncmaster_{name}")
+    spark_builder = SparkSession.builder.appName(f"SyncMaster__{name}")
 
-    for k, v in get_spark_session_conf(source, target, run.transfer.resources).items():
+    spark_session_config = settings.spark_session_default_config.copy()
+    spark_session_config.update(get_spark_session_conf(source, target, run.transfer.resources))
+
+    for k, v in spark_session_config.items():
         spark_builder = spark_builder.config(k, v)
 
     for entity in source, target: